Financial Risk Manager Part 1
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A hedge fund manager runs a regression for quarterly returns on a stock over 50 quarters against three independent variables P/Sales, P/E, and P/B. He generates the following results:
| Variable | Coefficient | p-Value |
|---|---|---|
| Intercept | 9.02 | 0.10 |
| P/Sales | 1.20 | 0.16 |
| P/E | 4.12 | 0.19 |
| P/B | 2.34 | 0.21 |
| R² | 90.12% |
The hedge fund manager has computed the sum of squared residual errors (SSR) as 20. What is the value of the standard error of the regression (SER)?
Other
Community
NNikitesh
A
0.6594
B
0.6523
C
0.9012
D
0.9158
Explanation:
Explanation
The standard error of the regression (SER), also known as the standard error of the estimate (SEE), is calculated using the formula:
Where:
- SSR = Sum of Squared Residuals = 20
- n = number of observations = 50 quarters
- k = number of independent variables = 3 (P/Sales, P/E, and P/B)
Plugging in the values:
Key points:
- The degrees of freedom for the regression is n - (k + 1), where k+1 accounts for all parameters estimated (k slope coefficients + 1 intercept)
- SSR represents the unexplained variation in the regression
- The R² value of 90.12% is not needed for this calculation
- The p-values and coefficients are also not needed for this calculation
This matches option A: 0.6594
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